Christopher Siviy

Assistance magnitude versus metabolic cost reductions for a tethered multiarticular soft exosuit

Evaluation of a soft exosuit designed to reduce metabolic requirements during walking. When defining requirements for any wearable robot for walking assistance, it is important to maximize the user’s metabolic benefit resulting from the exosuit assistance while limiting the metabolic penalty of carrying the system’s mass. Thus, the aim of this study was to isolate and characterize the relationship between assistance magnitude and the metabolic cost of walking while also examining changes to the wearer’s underlying gait mechanics. The study was performed with a tethered multiarticular soft exosuit during normal walking, where assistance was directly applied at the ankle joint and indirectly at the hip due to a textile architecture. The exosuit controller was designed such that the delivered torque profile at the ankle joint approximated that of the biological torque during normal walking. Seven participants walked on a treadmill at 1.5 meters per second under one unpowered and four powered conditions, where the peak moment applied at the ankle joint was varied from about 10 to 38% of biological ankle moment (equivalent to an applied force of 18.7 to 75.0% of body weight). Results showed that, with increasing exosuit assistance, net metabolic rate continually decreased within the tested range. When maximum assistance was applied, the metabolic rate of walking was reduced by 22.83 ± 3.17% relative to the powered-off condition (mean ± SEM).

IMU-based iterative control for hip extension assistance with a soft exosuit

In this paper we describe an IMU-based iterative controller for hip extension assistance where the onset timing of assistance is based on an estimate of the maximum hip flexion angle. The controller was implemented on a mono-articular soft exosuit coupled to a lab-based multi-joint actuation platform that enables rapid reconfiguration of different sensors and control strategy implementation. The controller design is motivated by a model of the suit-human interface and utilizes an iterative control methodology that includes gait detection and step-by-step actuator position profile generation to control the onset timing, peak timing, and peak magnitude of the delivered force. This controller was evaluated on eight subjects walking on a treadmill at a speed of 1.5 m/s while carrying a load of 23 kg. Results showed that assistance could be delivered reliably across subjects. Specifically, for a given profile, the average delivered force started concurrently with the timing of the maximum hip flexion angle and reached its peak timing 22.7 ± 0.63% later in the gait cycle (desired 23%) with a peak magnitude of 198.2 ± 1.6 N (desired 200 N), equivalent to an average peak torque of 30.5 ± 4.7 Nm. This control approach was used to assess the metabolic effect of four different assistive profiles. Metabolic reductions ranging from 5.7% to 8.5% were found when comparing the powered conditions with the unpowered condition. This work enables studies to assess the biomechanical and physiological responses to different assistive profiles to determine the optimal hip extension assistance during walking.

Lower Limb Biomechanical Analysis During an Unanticipated Step on a Bump Reveals Specific Adaptations of Walking on Uneven Terrains

ABSTRACT Although it is clear that walking over different irregular terrain is associated with altered biomechanics, there is little understanding of how we quickly adapt to unexpected variations in terrain. This study aims to investigate which adaptive strategies humans adopt when performing an unanticipated step on an irregular surface, specifically a small bump. Nine healthy male participants walked at their preferred walking speed along a straight walkway during five conditions: four involving unanticipated bumps of two different heights, and one level walking condition. Muscle activation of eight lower limb muscles and three-dimensional gait analysis were evaluated during these testing conditions. Two distinct adaptive strategies were found, which involved no significant change in total lower limb mechanical work or walking speed. An ankle-based strategy was adopted when stepping on a bump with the forefoot, whereas a hip-based strategy was preferred when stepping with the rearfoot. These strategies were driven by a higher activation of the plantarflexor muscles (6–51%), which generated a higher ankle joint moment during the forefoot conditions and by a higher activation of the quadriceps muscles (36–93%), which produced a higher knee joint moment and hip joint power during the rearfoot conditions. These findings provide insights into how humans quickly react to unexpected events and could be used to inform the design of adaptive controllers for wearable robots intended for use in unstructured environments that can provide optimal assistance to the different lower limb joints. Summary: Investigation of an unanticipated step on uneven ground reveals two distinct adaptive strategies: an ankle-based strategy when stepping with the forefoot, and a hip-based strategy when stepping with the rearfoot.

Comparison of Ankle Moment Inspired and Ankle Positive Power Inspired Controllers for a Multi-Articular Soft Exosuit for Walking Assistance

Mobility can be limited due to age or impairments. Wearable robotics provide the chance to increase mobility and thus independence. A powered soft exosuit was designed that assist with both ankle plantarflexion and hip flexion through a multi-articular suit architecture. So far, the best method to reduce metabolic cost of human walking with external forces is unknown. Two basic control strategies are compared in this study: an ankle moment inspired controller (AMIC) and an ankle positive power inspired controller (APIC). Both controllers provided a similar amount of average positive exosuit power and reduced the net metabolic cost of walking by 15 %. These results suggest that average positive power could be more important than assistive moment during single stance for reducing metabolic cost. Further analysis must show if one of the approaches has advantages for wearers comfort, changes in walking kinetics and kinematics, balance related biomechanics, or electrical energy consumption.

Evaluation of Force Tracking Controller with Soft Exosuit for Hip Extension Assistance

This abstract describes the design and experimental evaluation of a force tracking controller for hip extension assistance utilizing a soft exosuit connected to a tethered off-board actuation system. The new controller aims to improve the force profile tracking capability and demonstrate its advantages over our previously reported work. The controller was evaluated by one healthy participant walking on a treadmill at 1.35 m/s. Results showed that the system can deliver a predefined force profile robustly with a 200 N peak force. The measured peak force value using force controller was 198.7 ± 2.9 N, and the root-mean-squared (RMS) error was 3.4 N (1.7 % of desired peak force). These results indicate that the force control reduces peak force variability and improves force profile tracking capability.

Biomechanical Analysis and Inertial Sensing of Ankle Joint While Stepping on an Unanticipated Bump

Walking on uneven terrain with a wearable assistive robot requires the controller to adapt to rapid changes in human’s biomechanics. To do so, the changes due to terrain should be measured using wearable sensors. We investigated human ankle joint mechanics when stepping on different small, unanticipated bumps with either the forefoot or the rearfoot. It was shown that kinematics and kinetics change significantly depending on how humans step on a bump, and that changes in kinematics could be measured by IMUs. This result could be used to inform the design of adaptive controllers for wearable robots that provide optimal assistance to the ankle joint when walking on uneven terrain.